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20 results for “mixotrophic”
Figure 2 in Nitrogen-fixing Cyanothece sp. as a mixotroph and silver nanoparticle synthesizer: a multitasking exceptional cyanobacterium
Figure 2. Disc inhibition zone against MRSA Staphylococcus aureus using (a) gold nanoparticles, (b) silver nanoparticles, and (c) both silver nanoparticles and gold nanoparticles.
Microbiome, mixotrophic algae, zooplankton, and fish amino acid and phospholipid fatty acid content in terrestrial and plastic carbon treatments
<p>Data includes amino acid (µg AA mg DW<sup>-1</sup>) and phospholipid fatty acid content (µg FA mg DW<sup>-1</sup>) of the microbiome, mixotrophic algae, zooplankton, and fish<em> </em>from the four-trophic level experiment. The experiment included control (no addition), 13.5% <sup>13</sup>C-labelled beech leaves (<em>Fagus sylvatica</em>), 97% <sup>13</sup>C-labelled lignin-hemicellulose extracted from wheat (<em>Triticum aestivum</em>, ~80% lignin, 13% hemicellulose), and 99% <sup>13</sup>C-labelled polystyrene (microplastic). Incubation time in humic lake water was 14 days in the control, leaf, and lignin experiment but 56 days for polystyrene, which after mixotrophic algae (<em>Cryptomonas </em>sp.) was introduced to the bottles. In the next step, herbivorous zooplankton (<em>Daphnia magna</em>) consumed microbes, mixotrophic algae, and particles for five days which after they were used as the diet to zebrafish (<em>Danio rerio</em>) during a five-day experiment.</p>
Coadaptation shapes ecological interactions in mixotroph-resource systems
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Body size, light intensity and nutrient supply determine plankton stoichiometry in mixotrophic plankton food webs
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Prey morphotype and abundance controls plastid retention and bloom dynamics for a mixotrophic dinoflagellate
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Data from: Why do mixotrophic plants stay green? A comparison between green and achlorophyllous orchid individuals in situ
Some forest plants adapt to shade by mixotrophy, i.e., they obtain carbon both from photosynthesis and from their root mycorrhizal fungi. Fully achlorophyllous species using exclusively fungal carbon (the so-called mycoheterotrophic plants) have repeatedly evolved from such mixotrophic ancestors. However, adaptations for this evolutionary transition, and the reasons why it has happened a limited number of times, remain unknown. We investigated this using achlorophyllous variants (i.e., albinos) spontaneously occurring in Cephalanthera damasonium, a mixotrophic orchid. In two populations, we compared albinos with co-occurring green individuals in situ. We investigated vegetative traits, namely, shoot phenology, dormancy, CO2 and H2O leaf exchange, mycorrhizal colonization, degree of mycoheterotrophy (using 13C abundance as a proxy), and susceptibility to pathogens and herbivores. We monitored seed production (in natural or experimental crosses) and seed germination. Albinos displayed (1) more frequent shoot drying at fruiting, possibly due to stomatal dysfunctions, (2) lower basal metabolism, (3) increased sensitivity to pathogens and herbivores, (4) higher dormancy and maladapted sprouting, and, probably due to the previous differences, (5) fewer seeds, with lower germination capacity. Over the growing season, green shoots shifted from using fungal carbon to an increasingly efficient photosynthesis at time of fruiting, when fungal colonization reached its minimum. Conversely, the lack of photosynthesis in fruiting albinos may contribute to carbon limitation, and to the above-mentioned trends. With a 103× fitness reduction, albinos failed a successful transition to mycoheterotrophy because some traits inherited from their green ancestors are maladaptive. Conversely, mycoheterotrophy requires at least degeneration of leaves and stomata, optimization of the temporal pattern of fungal colonization and shoot sprouting, and new defenses against pathogens and herbivores. Transition to mycoheterotrophy likely requires progressive, joint evolution of these traits, while a sudden loss of photosynthesis leads to unfit plants. We provide explanations for the evolutionary stability of mixotrophic nutrition and for the rarity of emergence of carbon sinks in mycorrhizal networks. More broadly, this may explain what prevents the emergence of fully heterotrophic taxa in the numerous other mixotrophic plant or algal lineages recently described.
Data for replication of figures in "In situ imaging of a kleptoplastidic ciliate thin layer indicates traditional sampling underestimates oceanic mixotroph biomass", Barua et al. Communications Earth & Environment (2024).
<p>This dataset contains the relevant information needed to reproduce data plots in Figures 1-5 and Supplementary Figures 2-3 of the following manuscript.</p> <p><em><strong>In situ imaging of a kleptoplastidic ciliate thin layer indicates traditional sampling underestimates oceanic mixotroph biomass</strong></em></p> <p>Ranjoy Barua, Lisa Nyman, Buyu Guo, Matthew D. Johnson, Anvita U. Kerkar, Jiarong Hong, Adam T. Greer, John Lehrter, Malcolm McFarland, Bradley Penta, Aditya R. Nayak</p> <p>Communications Earth & Environment (2024).</p>
Data from: Modelling the consequence of glacier retreat on mixotrophic nanoflagellate bacterivory: a Bayesian approach
<p>This repository comprises data and statisticial analysis from the paper Schenone et al. 2020 entitled "Modelling the Consequence of Glacier Retreat on Mixotrophic Nanoflagellate Bacterivory: A Bayesian Approach" which was accepted for publication in Oikos. The main contribution of this paper is a model for mixotrophic nanoflagellate bacterivory as a function of light availability and the presence of non edible particles such as glacial clay. The dataset consists in results from eight bacterivory experiments carried out during November 2018 and January-February 2019 using natural mixotrophic nanoflagellate community of six moutain lakes from north Patagonia, Argentina. A Bayesian approach was adopted to estimate relevant parameters from the model using our experimental data. The analysis was performed using JAGS interfaced through R Studio, the script is available in this repository.</p>
Data from: Trophic plasticity of mixotrophic corals under contrasting environments
<p>1. Mixotrophic organisms can derive nutrition from both auto- and heterotrophy, which allows them to use a variety of trophic pathways to sustain their metabolic demands under variable conditions. Therefore, when facing environmental change, these organisms are expected to demonstrate an intrinsic ability to acclimatise through trophic plasticity.</p> <p>2. Scleractinian corals are ecologically important mixotrophs, but understanding their trophic plasticity has been impaired by an oversimplification toward inconsistent proxies of coral diet and overlooking intraspecific variability.</p> <p>3. Here, we applied a Bayesian analysis of carbon and nitrogen stable isotope data to determine the trophic niches of six common species of scleractinian corals and their associated endosymbionts, and combined it with an unsupervised machine learning algorithm to identify trophic behaviours and strategies.</p> <p>4. We found a variable amount of nutritional plasticity identified by different trophic behaviours within and between mixotrophic corals living under the same environmental conditions. Further, we observed changes in trophic plasticity across environmental conditions. Corals from variable environments had larger host and endosymbiont niches than corals from stable environments. In addition, deeper corals had niches indicating a greater degree of heterotrophy than shallow corals. Collectively, corals exhibited distinct trophic strategies by promoting trophic niche differentiation along the mixotrophic continuum and conspecific individual colonies displayed high trophic variation.</p> <p>5. Our results provide a foundation to understand how mixotrophic organisms may adjust their nutrition in response to ongoing global environmental change and the consequential modification of benthic assemblages.</p>
Data from: Trophic plasticity of mixotrophic corals under contrasting environments
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Data from: Why do mixotrophic plants stay green? A comparison between green and achlorophyllous orchid individuals in situ
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Data from: Modelling the consequence of glacier retreat on mixotrophic nanoflagellate bacterivory: a Bayesian approach
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Data from: Importance of mixotrophic bacterivory can be predicted by light and loss rates
Recent observational studies form oligotrophic waters provide ample evidence that mixotrophic flagellates often account for the bulk of bacterivory. However, we lack a general framework that allows a mechanistic understanding of success of mixotrophs in the competition with heterotrophic bacterivores. This is especially needed for integrating mixotrophy in models of the microbial loop. Based on general tradeoffs linked to the combined resource use in mixotrophs (generalist versus specialist), we propose a concept where mixotrophs are favored by conditions of high light – low losses, corresponding to the situation found in the surface waters of oligotrophic oceans. Under such conditions, they can achieve positive net growth at very low resource levels, allowing simultaneous competition with specialized protists. Conversely, heterotrophic bacterivores and photoautotrophs should be especially favored in more productive and low-light conditions. We show experimentally that the combined effect of light and loss rates (dilution) predicts the success of mixotrophic bacterivorous flagellates. Moreover, our results suggest that total bacterivory, contrary as seen in the traditional microbial loop concept, has a more intricate coupling to light.
Mixotrophic growth of a ubiquitous marine diatom
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Figure 1 in Nitrogen-fixing Cyanothece sp. as a mixotroph and silver nanoparticle synthesizer: a multitasking exceptional cyanobacterium
Figure 1. FTIR spectrum of biogenic silver nanoparticles from unfiltered external solution of Cyanothece sp.
Data from: Importance of mixotrophic bacterivory can be predicted by light and loss rates
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Transcriptomics reveal a unique phago-mixotrophic response to low nutrient concentrations in the prasinophyte Pterosperma cristatum
GEO Series GSE268495. Pterosperma cristatum. 15 samples. Type: Expression profiling by high throughput sequencing.
M. sedula transcriptional response under heterotrophic, autotrophic, and mixotrophic growth conditions
GEO Series GSE14978. Metallosphaera sedula. 7 samples. Type: Expression profiling by array.
Investigating mixotrophic metabolism in the model diatom Phaeodactylum tricornutum.
GEO Series GSE91004. Phaeodactylum tricornutum. 3 samples. Type: Expression profiling by array.
Cell-specific gene expression in Anabaena variabilis grown phototrophically, mixotrophically, and heterotrophically
GEO Series GSE46076. Trichormus variabilis ATCC 29413. 27 samples. Type: Expression profiling by array.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.